About this Research Topic
This Research Topic is part of the Machine Learning in Neuroscience series
Machine Learning in Neuroscience
In recent years, machine learning, and artificial intelligence algorithms have been utilized in solving fascinating problems in different fields of science, including neuroscience. In this research topic, we are seeking to bring together researchers who are using machine learning methods to address neuroscientific questions or who are devising artificial neural networks based on known connectivity and plasticity rules in the nervous system. More specifically, this collection of articles is intended to cover recent directions and activities in the field of machine learning, especially the recent paradigm of deep learning, in neuroscience dedicated to analysis, diagnosis, and modeling of the neural mechanisms of brain functions. Furthermore, the research topic aims to stimulate collaboration between researchers in various fields of neuroscience and artificial intelligence.
We welcome submissions of original neuroscience research papers from a range of different specialties such as cognitive and systems neuroscience to neuroimaging and neural signal processing. Original research and reviews, as well as theoretical work, methods, and modeling articles are welcomed. The research work may include experimental studies using state-of-the-art in electrophysiology and neuroimaging techniques as well as experimental based computational or theoretical work.
Keywords: Machine Learning, Deep Learning, Image and Signal Processing, Brain Functional Modeling, Computational Neuroscience, Artificial Intelligence
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.